Bayani Atiyeh, Nazarimehr Fahimeh, Jafari Sajad, Kovalenko Kirill, Contreras-Aso Gonzalo, Alfaro-Bittner Karin, Sánchez-García Rubén J, Boccaletti Stefano
Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
Health Technology Research Institute, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.
Nat Commun. 2024 Jun 10;15(1):4955. doi: 10.1038/s41467-024-48203-6.
We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the graph Laplacian matrix. The transition comes out to be made of a well defined sequence of events, each of which corresponds to a specific clustered state. The network's nodes involved in each of the clusters can be identified, and the value of the coupling strength at which the events are taking place can be approximately ascertained. Finally, we present large-scale simulations which show the accuracy of the approximation made, and of our predictions in describing the synchronization transition of both synthetic and real-world large size networks, and we even report that the observed sequence of clusters is preserved in heterogeneous networks made of slightly non-identical systems.
我们研究了一般网络动力系统的同步特性,并表明,在适当的近似下,仅借助图拉普拉斯矩阵的特征值和特征向量就能预测向同步的转变。结果表明,这种转变由一系列定义明确的事件组成,每个事件都对应于一种特定的聚类状态。可以识别出每个聚类中涉及的网络节点,并且可以大致确定事件发生时的耦合强度值。最后,我们进行了大规模模拟,结果表明所做近似以及我们在描述合成和现实世界大型网络同步转变方面的预测具有准确性,我们甚至报告称,在由略有不同的系统组成的异构网络中,观察到的聚类序列得以保留。